Πρόβλεψη πωλήσεων σε αλυσίδα καταστημάτων τυχερών παιχνιδιών με την χρήση προηγμένων μεθόδων αναλυτικής & οπτικοποίησης
Revenue forecasting using advanced analytical & visualization methods in retail betting company
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Keywords
Revenue forecasting ; Big data ; Visualization ; Quantitative forecastingAbstract
This thesis explores the use of advanced analysis, visualization and forecasting methods to improve
revenue forecasting in a betting company. The study aims to develop a reliable and accurate revenue
forecasting model to support decision making and strategic planning in the company. The research
methodology includes the collection of historical sales data from the stores and the application of
various statistical techniques, including time series analysis, regression analysis, etc. In addition to
store sales data, different data sets such as demographics or points of interest are considered to
support this analysis and verify the generated results. The study also examines the impact of external
factors such as competition, economic trends and marketing campaigns on revenue forecast
accuracy. The results show that the proposed prediction model outperforms traditional methods in
terms of accuracy and reliability. The study concludes that the application of advanced analysis and
forecasting methods can significantly improve revenue forecasting in gaming stores and help
companies make informed decisions in a competitive market.